This invention relates generally to computer analysis and more particularly to CFD analysis of aeroacoustic properties. Computational Fluid Dynamics (CFD) is a branch of fluid dynamics in which the physics of motion of particles of gases or liquids are simulated using computers. The physical volume of fluid and bounding surfaces are represented using a finite set of discrete elements, and mathematical equations relating the motion of particles are computed at each element. Commercial CFD software is currently used in industry for a broad range of applications, including internal flow of liquids and gases in pipes, machinery, ventilation ducts, etc., as well as external flow of air or water for application to land, air and sea vehicles.
A common thread to uses of CFD in applications is the presence of turbulence in the results. Turbulence occurs naturally in fluids as a result of the complex non-linearities in the physical relationship between inertia of moving fluid particles, and the resistance to motion provided by friction (also called viscosity or viscous force). A fluid dynamic parameter called the Reynolds number is the ratio between inertial and viscous force. Every flow configuration has a critical Reynolds number above which the flow becomes turbulent, and below which the flow is smooth and ordered, or laminar. One definition of turbulence is flow that contains a range of spatial and temporal scales extending from the largest physical scales of the problem, represented by the size of the geometry and time scale of any forcing or motion, to the smallest possible scale allowed by fluid dynamics, which is called the Komolgorov scale, and is determined by the viscosity of the fluid. In physical applications, one sees large-scale fluid dynamic variations, superimposed by “eddies” of various sizes down to the smallest measurable scale. One representation of this superposition is a spectrum, computed from the kinetic energy of the flow at a single point in space as a function of time. This spectrum shows high energy contributions at some low frequency related to the scale of the physical problem, and then a “cascade” of energy to smaller and smaller scales (higher frequencies on the spectrum), with lower and lower energy levels.
Some prior art CFD software attempts to represent turbulence in terms of its mean contribution to the flow using an aggregate “turbulence model”. In these software programs, the actual turbulence phenomenon is not visible in the results, and the results typically only show the flow time-averaged over long segments of time relative to the temporal scale of turbulence. However, modern commercial software is moving toward more intensive simulations of the physical phenomena involved in fluid dynamics, and including a significant portion of the turbulent energy spectrum in the resulting data. This means that the flow data contains spatial and temporal scales extending down to the smallest scales that can be resolved using the computational model of the fluid particles, while smaller scales yet beyond that level are considered only using a mathematical average effect.
While current CFD software can produce this enormous wealth of data, tools to understand this data are lacking. In fact, the CFD software is still relatively young and improvements to the physical models are still underway to simply improve the aggregate predictions using these software tools. Meanwhile, users have available to them this turbulent data, and have interest in understanding the important flow features which have some bearing on performance of their products. Some particular areas of interest in which turbulent flow features at various scales are important are wakes, mixing, combustion, vibration and noise. Examples are the turbulent wake of an aircraft, vibration of rotating disk drives, and wind noise on an automobile. Accordingly, there is a need for software which provides analysis and visualization of turbulent CFD computational results.